FUEL is a hierarchical framework for Fast UAV ExpLoration.
It contains a Frontier Information Structure (FIS), which can be incrementally updated with the online built map and facilitate exploration planning in high frequency.
Based on FIS, a hierarchical planner plans optimal global coverage paths, refine local viewpoints, and generates minimum-time local trajectories successively.
Our method is demonstrated to complete challenging exploration tasks 3-8 times faster than state-of-the-art approaches.
Authors: Boyu Zhou and Shaojie Shen from the HUKST Aerial Robotics Group.
Complete videos: video1.
Please cite our paper if you use this project in your research:
- FUEL: Fast UAV Exploration using Incremental Frontier Structure and Hierarchical Planning, Boyu Zhou, Yichen Zhang, Xinyi Chen, Shaojie Shen, IEEE Robotics and Automation Letters (RA-L) with ICRA 2021 option
@article{zhou2021fuel,
title={FUEL: Fast UAV Exploration Using Incremental Frontier Structure and Hierarchical Planning},
author={Zhou, Boyu and Zhang, Yichen and Chen, Xinyi and Shen, Shaojie},
journal={IEEE Robotics and Automation Letters},
volume={6},
number={2},
pages={779--786},
year={2021},
publisher={IEEE}
}
Please kindly star ⭐ this project if it helps you. We take great efforts to develope and maintain it 😁😁.
This project is mostly based on Fast-Planner. It has been tested on Ubuntu 16.04(ROS Kinetic) and 18.04(ROS Melodic). Take Ubuntu 18.04 as an example, run the following commands to setup:
sudo apt-get install libarmadillo-dev ros-melodic-nlopt
To simulate the depth camera, we use a simulator based on CUDA Toolkit. Please install it first following the instruction of CUDA.
After successful installation, in the local_sensing package in uav_simulator, remember to change the 'arch' and 'code' flags in CMakelist.txt according to your graphics card devices. You can check the right code here. For example:
set(CUDA_NVCC_FLAGS
-gencode arch=compute_61,code=sm_61;
)
Finally, clone and compile our package:
cd ${YOUR_WORKSPACE_PATH}/src
git clone https://github.com/HKUST-Aerial-Robotics/FUEL.git
cd ../
catkin_make
After compilation you can start the visualization by:
source devel/setup.bash && roslaunch exploration_manager rviz.launch
and start a simulation (run in a new terminals):
source devel/setup.bash && roslaunch exploration_manager exploration.launch
You will find a cluttered scene to be explored (20m x 12m x 2m) and the drone in Rviz. You can trigger the exploration to start by the 2D Nav Goal tool. A sample simulation is shown in the figure. The unknown obstacles are shown in grey, while the frontiers are shown as colorful voxels. The planned and executed trajectories are also displayed.
We use NLopt for non-linear optimization and use LKH for travelling salesman problem.